Machine and equipment assets are engineered to perform particular tasks as part of a business process. For example, assets can include, among other things and without limitation, industrial manufacturing equipment on a production line, drilling equipment for use in mining operations, wind turbines that generate electricity on a wind farm, transportation vehicles, and the like. As another example, assets may include devices that aid in diagnosing patients such as imaging devices (e.g., X-ray or MRI systems), monitoring equipment, and the like. The design and implementation of these assets often takes into account both the physics of the task at hand, as well as the environment in which such assets are configured to operate.
Low-level software and hardware-based controllers have long been used to drive machine and equipment assets. However, the rise of inexpensive cloud computing, increasing sensor capabilities, and decreasing sensor costs, as well as the proliferation of mobile technologies, have created opportunities for creating novel industrial and healthcare based assets with improved sensing technology and which are capable of transmitting data that can then be distributed throughout a network. As a consequence, there are new opportunities to enhance the business value of some assets through the use of novel industrial-focused hardware and software.
As technology develops, it may be desirable or necessary to emulate one or more hardware devices in software. One such situation arises when hardware and/or software becomes outdated (referred to as legacy hardware or code), but the older hardware is needed to perform software debug and development. Typically, a conventional hardware emulator or debugger must be plugged into a target system via an external pod (e.g., external hardware) that connects to numerous device pins in order to interface with the target system. This is cumbersome and time consuming. In most cases, it is also unlikely that a debugger can be installed to a product installed on an asset.